1. Lecture 11: Cache Hierarchies
Today: cache access basics and innovations
(Sections B.1-B.3, 2.1)
HW4 due on Thursday
Office hours on Wednesday 10am – 11am, 12-1pm
TA office hours on Wednesday, 3-4pm
Midterm next week, open book, open notes, material
in first ten lectures (excludes this week)

2. The Cache Hierarchy
Core L1 L2 L3
Off-chip memory

3. Accessing the Cache Byte address 101000 Offset 8-byte words
8 words: 3 index bits
Direct-mapped cache:
each address maps to
a unique address
Sets
Data array

4. The Tag Array Byte address 101000 Tag 8-byte words Compare
Direct-mapped cache:
each address maps to
a unique address
Tag array
Data array

5. Increasing Line Size Byte address
A large cache line size  smaller tag array,
fewer misses because of spatial locality
32-byte cache
line size or
block size
Tag
Offset
Tag array
Data array

6. Associativity Byte address
Set associativity  fewer conflicts; wasted power
because multiple data and tags are read
Tag
Way-1
Way-2
Tag array
Data array
Compare

7. Example 32 KB 4-way set-associative data cache array with 32
byte line sizes
How many sets?
How many index bits, offset bits, tag bits?
How large is the tag array?

8. Types of Cache Misses
Compulsory misses: happens the first time a memory
word is accessed – the misses for an infinite cache
Capacity misses: happens because the program touched
many other words before re-touching the same word – the
misses for a fully-associative cache
Conflict misses: happens because two words map to the
same location in the cache – the misses generated while
moving from a fully-associative to a direct-mapped cache
Sidenote: can a fully-associative cache have more misses
than a direct-mapped cache of the same size?

9. What Influences Cache Misses?
Compulsory
Capacity
Conflict
Increasing cache capacity
Increasing number of sets
Increasing block size
Increasing associativity

10. Reducing Miss Rate
Large block size – reduces compulsory misses, reduces
miss penalty in case of spatial locality – increases traffic
between different levels, space wastage, and conflict misses
Large caches – reduces capacity/conflict misses – access
time penalty
High associativity – reduces conflict misses – rule of thumb:
2-way cache of capacity N/2 has the same miss rate as
1-way cache of capacity N – more energy

11. Cache Misses On a write miss, you may either choose to bring the block
into the cache (write-allocate) or not (write-no-allocate)
On a read miss, you always bring the block in (spatial and
temporal locality) – but which block do you replace?
no choice for a direct-mapped cache
randomly pick one of the ways to replace
replace the way that was least-recently used (LRU)
FIFO replacement (round-robin)

12. Writes When you write into a block, do you also update the copy in L2?
write-through: every write to L1  write to L2
write-back: mark the block as dirty, when the block
gets replaced from L1, write it to L2
Writeback coalesces multiple writes to an L1 block into one
L2 write
Writethrough simplifies coherency protocols in a
multiprocessor system as the L2 always has a current
copy of data

13. Reducing Cache Miss Penalty
Multi-level caches
Critical word first
Priority for reads
Victim caches

14. Multi-Level Caches
The L2 and L3 have properties that are different from L1
access time is not as critical for L2 as it is for L1 (every
load/store/instruction accesses the L1)
the L2 is much larger and can consume more power
per access
Hence, they can adopt alternative design choices
serial tag and data access
high associativity

15. Read/Write Priority
For writeback/thru caches, writes to lower levels are placed
in write buffers
When we have a read miss, we must look up the write
buffer before checking the lower level
When we have a write miss, the write can merge with
another entry in the write buffer or it creates a new entry
Reads are more urgent than writes (probability of an instr
waiting for the result of a read is 100%, while probability of
an instr waiting for the result of a write is much smaller) –
hence, reads get priority unless the write buffer is full

16. Victim Caches A direct-mapped cache suffers from misses because
multiple pieces of data map to the same location
The processor often tries to access data that it recently
discarded – all discards are placed in a small victim cache
(4 or 8 entries) – the victim cache is checked before going
to L2
Can be viewed as additional associativity for a few sets
that tend to have the most conflicts

17. Tolerating Miss Penalty
Out of order execution: can do other useful work while
waiting for the miss – can have multiple cache misses
-- cache controller has to keep track of multiple
outstanding misses (non-blocking cache)
Hardware and software prefetching into prefetch buffers
– aggressive prefetching can increase contention for buses

18. Title
Bullet